Jason Simon discusses how global trade can contribute to a better society

Just a few years ago, most economists and political leaders would have agreed: free trade policies are better than trade protectionism. However, that is no longer the case; major economies are moving away from regional and international economic integration, claiming that it has lowered people’s standard of living or diminished sovereign political control. Jason Simon, a FinTech and cryptocurrency specialist, explains the different ways in which society can improve through global trade and how it can be seen from different perspectives worldwide.

The US has moved from rhetorical protectionism to unilateral action, imposing tariffs on China and other major trading partners, leading to retaliatory tariffs. The UK’s exit from the European Union represent a departure from the world’s most deeply integrated transnational market.

The controversy over trade appears to be ironic. First of all, it occurs most strongly within some advanced economies, especially the United States, which until very recently had been the prime movers of the liberal trade order in the post-1945 era. Second, trade has become an issue of contention just when it should be enjoying a moment of triumph: free trade has been a key component in the rapid growth and development of the past forty years, which has lifted billions of people around the world out of extreme poverty.

However, the backlash against trade does not seem so surprising. Despite the many benefits of economic globalization-which has been the fastest poverty reducer in history-many people, including those in the world’s richest countries, have reasonable cause to feel that they have been left out.

Simon explains, “Closing markets to trade and investment is not the solution: it would leave us collectively poorer and fuel political anger rather than alleviate it. The goal must be to harness the prosperity that trade can foster to create win-win societies. In order to understand how we got here, and where to go, we need to examine what we have done well in the global economy and where we have fallen short.” The free exchange of goods, services, and data has interconnected countries with unprecedented intensity, spurring transformative changes in the global economy.

The rapid expansion of global trade that began in the ’80s was driven by market-oriented reforms in China, India, and the former Soviet bloc, combined with falling trade costs. This fall was the consequence of certain policy changes, including a reduction of tariffs and non-tariff barriers to trade, and also of certain advances in transportation and communication technology. Progressively, more and more free trade policies were consolidated thanks to the multilateral trade rules established in the General Agreement on Tariffs and Trade and, since 1995, in the World Trade Organization.

Asserts Simon, “Easier entry into world markets proved especially valuable for developing countries, where tradable product sectors tend to be more productive than non-tradable activities. Open world markets allow countries with small domestic markets to use external demand to divert personnel and resources from subsistence activities to the production of tradable, and therefore more productive, goods and services. The result is an increase in the overall productivity of the economy.”

The arguments in favor of a cooperative approach to trade, implicit in multilateral rules and institutions, go far beyond basic short-term issues. Climate change, migration, cybersecurity, terrorism, and pandemic diseases have cross-border implications that require cooperative responses from countries. Governments that develop negative-sum strategies for trade and investment will have to work very hard to achieve positive-sum results on these other challenges.

The perception among a large number of people that the economy is not working has fueled logical resentment. And trade is a handy scapegoat for venting this indignation. Foreigners – the goods and services they produce, the jobs they supposedly fill – are tangible objects to blame. Other factors affecting people’s job prospects go unnoticed: machines and software that quietly improve year after year, for example, or domestic policy decisions that fail to adequately train people to benefit from economic change.

Related Post

  • bitcoinBitcoin (BTC) $ 70,296.00 0.94%
  • ethereumEthereum (ETH) $ 3,562.70 1.07%
  • tetherTether (USDT) $ 0.999307 0.05%
  • bnbBNB (BNB) $ 609.78 3.69%
  • solanaSolana (SOL) $ 187.32 1.9%
  • staked-etherLido Staked Ether (STETH) $ 3,557.57 1.41%
  • xrpXRP (XRP) $ 0.619881 1.29%
  • usd-coinUSDC (USDC) $ 0.998683 0.19%
  • dogecoinDogecoin (DOGE) $ 0.214401 8.48%
  • cardanoCardano (ADA) $ 0.647122 0.43%
  • avalanche-2Avalanche (AVAX) $ 54.03 0.06%
  • shiba-inuShiba Inu (SHIB) $ 0.000031 1.65%
  • the-open-networkToncoin (TON) $ 4.89 1.17%
  • polkadotPolkadot (DOT) $ 9.45 0.19%
  • bitcoin-cashBitcoin Cash (BCH) $ 571.61 6.13%
  • chainlinkChainlink (LINK) $ 18.97 1.65%
  • wrapped-bitcoinWrapped Bitcoin (WBTC) $ 70,359.00 1.31%
  • tronTRON (TRX) $ 0.120470 0.84%
  • uniswapUniswap (UNI) $ 12.70 2.99%
  • matic-networkPolygon (MATIC) $ 0.994814 1.67%
  • internet-computerInternet Computer (ICP) $ 17.44 2.49%
  • nearNEAR Protocol (NEAR) $ 7.07 2.76%
  • litecoinLitecoin (LTC) $ 93.78 1.54%
  • aptosAptos (APT) $ 17.03 5.02%
  • leo-tokenLEO Token (LEO) $ 6.05 0.41%
  • blockstackStacks (STX) $ 3.51 3.81%
  • filecoinFilecoin (FIL) $ 9.37 3.38%
  • daiDai (DAI) $ 0.999415 0%
  • cosmosCosmos Hub (ATOM) $ 12.21 1.68%
  • ethereum-classicEthereum Classic (ETC) $ 32.32 0.95%
  • arbitrumArbitrum (ARB) $ 1.65 0.33%
  • immutable-xImmutable (IMX) $ 2.95 1.35%
  • render-tokenRender (RNDR) $ 10.92 1.85%
  • crypto-com-chainCronos (CRO) $ 0.152802 3.58%
  • stellarStellar (XLM) $ 0.139131 3.01%
  • hedera-hashgraphHedera (HBAR) $ 0.114798 2.16%
  • okbOKB (OKB) $ 64.25 0.19%
  • the-graphThe Graph (GRT) $ 0.404642 1.46%
  • mantleMantle (MNT) $ 1.17 1.76%
  • optimismOptimism (OP) $ 3.70 1.13%
  • dogwifcoindogwifhat (WIF) $ 3.74 20.37%
  • bittensorBittensor (TAO) $ 523.72 4.44%
  • makerMaker (MKR) $ 3,638.91 7.81%
  • injective-protocolInjective (INJ) $ 37.53 1.45%
  • fetch-aiFetch.ai (FET) $ 3.19 3.12%
  • vechainVeChain (VET) $ 0.045669 4.26%
  • pepePepe (PEPE) $ 0.000008 3.1%
  • kaspaKaspa (KAS) $ 0.138119 2.63%
  • thorchainTHORChain (RUNE) $ 9.21 1.85%
  • theta-tokenTheta Network (THETA) $ 2.95 0.45%